International Journal of Advanced Computational Engineering and Networking, ISSN: 2320-2106, Volume-4, Issue-7, Jul.-2016 WSN FOR EARTHQUAKE DETECTION AND DAMAGE DETECTION SYSTEM 1 PRATIKSHA KAMBLE, 2S.M.GAJBHIYE 1 M.Tech, 2Assistant Professor, Electronics & Telecommunication Engineering Department, GCOE Amravati, Maharashtra, INDIA E-mail: [email protected], [email protected] Abstract— An earthquake consists of primary and secondary waves. These waves waves have travelled from the epicentre to recombine at the recording site as a function of their respective velocities, focal distances, and propagation paths. Body waves propagate within a body of rock and appear in the first arrival. . The combination of their peak velocities, peak accelerations, and duration of time they persist cause significant damage to infrastructures .so we have great need of constructing the wireless sensor network for detecting earthquake .because it has great potential to monitor at unprecedented spatial and temporal scales. With the help of wireless sensor network it is possible to reduce the damage by creating the alert system. Keywords— WSN, Primary, Secondary Wave, Peak Velocity, Peak Acceleration. information is needed to localize and evaluate the earthquake range and impact. False alarms should be filtered out. I. INTRODUCTION Earthquake early warning system (EEW) is of huge interest as the general public is less and less willing to accept that earthquake damage to lives and properties is a fate to bear. Carrying high social and commercial value, high speed railway lines stand at the weakness point for the public to endure such fate if earthquake happens. There are many earthquake early warning systems. The key of the EEW is an accurate and timely report of earthquake warning under such constraints as geographical and geological prediction limitation, communication constraints, fault tolerance; to name but a few. A. Seismic Waves All earthquakes are made of two types of wave. The P-wave compresses the earth as it moves, like a sound wave. It moves fast but does not cause much damage. The S-wave that follows deforms rock up and down like an ocean wave. It delivers most of the tremor’s violent energy .The fastest among these body waves is the primary or P-wave. The P-wave is the first elastic wave to reach the recording site. The secondary arrival contains body and surface waves such as S, Rayleigh, and Love waves. These later arriving waves often produce both horizontal and vertical ground motion. The combination of their peak velocities, peak accelerations, and duration of time they persist cause significant damage to infrastructures. As P-wave arrive onset of an earthquake, there are systems built for earthquake monitoring using P-wave based technique Wireless sensor network (WSN) is used in many domains due to its advantage in cost, simple maintenance, robustness, etc. There are calls to use WSN for EEW in recent years. In this paper, we first present a modular designed WSN framework for EEW. In this framework, we study two bottlenecks of applying WSN to EEW. First, we study the locations that the sensors should be placed (or the sensor density), so as to achieve a timely warning report and system efficiency. We observe that wireless communication is faster than the destructive S-wave of the earthquake. Therefore, a trade-off can be made so that the number of the sensors to be deployed or maintained can be significantly reduced. Intrinsically, the faster P-wave of the earthquake should first hit at least one sensor which can gather, compute and transmit this information to the damage prone point, before the S-wave arrives. Second, we study a deadline driven strategy for WSN to reduce false alarms. In this case, the WSN of EEW and the WSN of the railway line health monitoring system will work together. Since the sensors of the railway line health monitoring system of the railway lines are densely deployed, there will be a great number of reports generated. An early aggregation of the B. Causes of Earthquakes Most earthquakes are causally related to compressional or tensional stresses built up at the margins of the huge moving lithospheric plates that make up the earth's surface. The immediate cause of most shallow earthquakes is the sudden release of stress along a fault, or fracture in the earth's crust, resulting in movement of the opposing blocks of rock past one another. These movements cause vibrations to pass through and around the earth in wave form, just as ripples are generated when a pebble is dropped into water. Volcanic eruptions, rock falls, landslides, and explosions can also cause a quake, but most of these are of only local extent. Shock waves from a powerful earthquake can trigger smaller earthquakes in a distant location hundreds of miles away if the geologic conditions are favourable. WSN For Earthquake Detection and Damage Detection System 47 International Journal of Advanced Computational Engineering and Networking, ISSN: 2320-2106, Volume-4, Issue-7, Jul.-2016 detects earliest onset of an earthquake before damaging ground shaking occurs .The Earthquake Warning System comprises of a base station unit and a base node. The seismic data is logged and processed in real time in the sensor unit. The base unit controls relays and is connected to the server. The base node unit consist of an one arduino, Bluetooth module i.e. wireless message. The node consist of the different fusion of sensor. A graphical illustration is presented C. Damage Caused by Earthquakes The effects of an earthquake are strongest in a broad zone surrounding the epicenter. Surface ground cracking associated with faults that reach the surface often occurs, with horizontal and vertical displacements of several yards common. Such movement does not have to occur during a major earthquake; slight periodic movements called fault creep can be accompanied by micro earthquakes too small to be felt. The extent of earthquake vibration and subsequent damage to a region is partly dependent on characteristics of the ground. For example, earthquake vibrations last longer and are of greater wave amplitudes in unconsolidated surface material, such as poorly compacted fill or river deposits; bedrock areas receive fewer effects. II. WARNING SYSTEM ANALYSIS The high precision sensor with trending advancements technology, dedicated damage mitigation control systems can be made. These systems can not only record seismic activity but can also take control measures to alleviate the disastrous effects of a catastrophic seismic event on critical infrastructures. Developing such a site-specific EWS that works on a threshold based triggering algorithm. In this site specific approach, seismic signals are processed locally for determining instantaneous tremor magnitude of earthquake. This approach is suitable because it intend to install the system on-site for damage mitigation in a EWS facilitated infrastructure, rather than a regional paradigm approach which takes into account the measurement of complex earthquake parameters e.g. locating epicenters, depth etc. The EWS can effectually be implemented in sensitive sites such as next to a nuclear reactor or a chemical depot. Use of embedded system keeps the development cost low, so that the system can be made available to households in earthquake prone zones in underdeveloped countries. It attempt to observe the beginning of the ground motion (mainly P wave) at the site using direct sensor fusion technology to detect the ensuing, weak ground motion. At the same site, no attempt is necessarily made to locate the event and estimate the magnitude. The system comprises of dual sensor monitoring the three components of peak ground acceleration (PGA) motion (east-west, north-south, and up down). The use of a high sensitivity microelectromechanical sensor (MEMS) allows fine recording of the PGA. Simultaneously, a piezoelectric sensor feeds vital data into the sensor fusion algorithm, allowing rejection of false alarms and issuing alerts that are more reliable. Figure.1 Base station in order to constructing an alert system the transmission of seismic signal is necessary from one place to other. so one base station is here for recording the all seismic signals. And the node where all sensors are embedded in it for measuring the changes which are generated by earthquake. The first sensor is the accelerometer which act as a MEMS sensor for fine recording of the peak ground acceleration. The second sensor is a piezoelectric sensor, which is a piezofilm element laminated to a sheet of polyester (Mylar). It can produce a useable electrical signal output when forces (in this case ground movement) are applied to the sensing area. The third sensor is the temperature and humidity sensor. IV. PROPOSED METHODS: In this work developing an earthquake warning and protection system through P-wave sensing that Figure.2 Base node WSN For Earthquake Detection and Damage Detection System 48 International Journal of Advanced Computational Engineering and Networking, ISSN: 2320-2106, In case of volcanic eruption, the temperature of the surrounding changes, so it is captured by this dht11.PIR i.e. pyroelectric infrared sensor which detects human motion. Human body continuously emit heat and this heat is measured by the PIR sensor. Whenever the seismic wave occurs ,the change of parameter is observed by this fusion of sensor and all the data is recorded in the GRAPHIC USER INTERFACFE. Base station and base node is connected by the wireless message (by various wireless modules) and it is displayed and saved on the GUI. It is in the excel sheet and made using PLXDAQ software. Volume-4, Issue-7, Jul.-2016 B. Otuput on Excel Figure .5 C. Output in Terms of Graph Figure .6 Graph is plotted for different sensors. Each colour represent behavior of the different sensor. CONCLUSIONS The damage caused by the earthquake is unmeasurable as it is the one of the biggest natural calamities. The alert system helps to knowing the seismic activity before time and it helps to overcome the problem. In this seismic networked sensors ,the system can allow simpler implementation and low power hardware. It provides the information about the characterstics of the ground motion, either spectrum or time and trigger to minimize the damage. Use of embedded system keeps the development cost low so that the system can be made available to households in earthquake prone zones in underdeveloped countries. Figure.3 complete wireless sensor network V. RESULTS The temperature sensor will give the direct reading. The accelerometer gives the three dimensional coordinate i.e. the digital output. If the person is detected by the PIR motion sensor then it will give output 1 on the excel sheet, same as that of piezoelectric sensor, whenever the pressure is applied by external body it will generate voltage and gives output 1. REFERENCES A. Graphic User Interface [1] [2] [3] [4] [5] Figure .4 Nakamura, “On the urgent earthquake detection and alarm system (UrEDAS),” in Proc. 9th WCEE, Kyoto-Japan, 1988, pp. 673-678. Y. Nakamura, “Earthquake alarm system for Japan Railways,” Japanese Railway Engineering, 109: pp. 1-7, 1989. H. Kanamori. (2005). “Real Time Seismology and Earthquake Damage Mitigation.” Annu. Rev. Earth Planet. Sci., 33: pp. 195-214, L. Wald, “Data Fusion: A Conceptual Approach for an Efficient Exploitation of Remote Sensing Images,” in Proc. 2nd International Conference: Fusion of Earth Data, Sophia Antipolis, France, 1998. B.V. Dasarathy, “Sensor fusion potential exploitationinnovative architectures and illustrative applications,” in WSN For Earthquake Detection and Damage Detection System 49 International Journal of Advanced Computational Engineering and Networking, ISSN: 2320-2106, [6] [7] [8] [9] Proc. IEEE, vol. 85, no. 1, Jan 1997, doi: 10.1109/5.554206. R. Wei, Z. Tao, Z. Hai-yun, W. Lei-gang, Z. Yong-jie, L. Meng-kai, L.Hui-feng, and S. Jing-wei, “A research on calibration of low-precision MEMS inertial sensors,” in Proc. CCDC, pp. 3243-3247, May 2013, doi: 10.1109/CCDC.2013.6561506. D.J. Wald, V. Quitoriano, T.H. Heaton, and H. Kanamori, “Relationship between Peak Ground Acceleration, Peak Ground Velocity, and Modified Mercalli Intensity in California,” Earthquake Spectra, 1999b. Y. Song, Z. Wang, and Y. Du, “Theoretical and Experimental Research on Piezoelectric Sensors Response to Dynamic Strain,” in Proc. 8th ICEMI, 2007, pp. 194198, doi: 10.1109/ICEMI.2007.4351115. B. Allan, “The Neyman-Pearson Theory as Decision Theory, and as Inference Theory; With a Criticism of the [10] [11] [12] [13] [14] WSN For Earthquake Detection and Damage Detection System 50 Volume-4, Issue-7, Jul.-2016 Lindley-Savage Argument for Bayesian Theory,” Synthese, vol.36 (1), pp. 19-49, Sep. 1977. U.S. Geological Survey. Bay of Bengal [map]. Advanced National Seismic System, ShakeMap, Global Region, [Online].Availablehttp://earthquake.usgs.gov/earthquakes/ eventpage/usb000qy82#shakema p_pga Narasimha Prasad L V Shankar Murthy P Kishor Kumar Reddy C “Analysis of Magnitude for Earthquake Detection using Primary Waves and Secondary Waves”. Masafumi hosokawa , Byeong-pyo jeong , Osamu takizawa “earthquake intensity estimation and damage detection using remote sensing data for global rescue operations”. Takeshi Sakaki, Makoto Okazaki, and Yutaka Matsuo “Tweet Analysis for Real-Time Event Detection and Earthquake Reporting System Development”. Rui Tan Guoliang Xing Jinzhu Chen Wen-Zhan Song Renjie Huang“Quality-driven Volcanic Earthquake Detection using Wireless Sensor Networks”.
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